14,963 research outputs found
Temporal effects in trend prediction: identifying the most popular nodes in the future
Prediction is an important problem in different science domains. In this
paper, we focus on trend prediction in complex networks, i.e. to identify the
most popular nodes in the future. Due to the preferential attachment mechanism
in real systems, nodes' recent degree and cumulative degree have been
successfully applied to design trend prediction methods. Here we took into
account more detailed information about the network evolution and proposed a
temporal-based predictor (TBP). The TBP predicts the future trend by the node
strength in the weighted network with the link weight equal to its exponential
aging. Three data sets with time information are used to test the performance
of the new method. We find that TBP have high general accuracy in predicting
the future most popular nodes. More importantly, it can identify many potential
objects with low popularity in the past but high popularity in the future. The
effect of the decay speed in the exponential aging on the results is discussed
in detail
Current rectification by asymmetric molecules: An ab initio study
We study current rectification effect in an asymmetric molecule
HOOC-CH-(CH) sandwiched between two Aluminum electrodes using
an {\sl ab initio} nonequilibrium Green function method. The conductance of the
system decreases exponentially with the increasing number of CH. The
phenomenon of current rectification is observed such that a very small current
appears at negative bias and a sharp negative differential resistance at a
critical positive bias when . The rectification effect arises from the
asymmetric structure of the molecule and the molecule-electrode couplings. A
significant rectification ratio of 38 can be achieved when .Comment: to appear in J. Chem. Phy
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